Triple
T11596048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peggy Guggenheim |
E275003
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Laurence Vail |
E357454
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Laurence Vail | Statement: [Peggy Guggenheim, spouse, Laurence Vail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laurence Vail Context triple: [Peggy Guggenheim, spouse, Laurence Vail]
-
A.
Laurence Vail
chosen
Laurence Vail was an American writer and sculptor associated with the early 20th-century avant-garde and expatriate literary circles in Europe.
-
B.
Laurence Sharp
Laurence Sharp is an individual notable enough to be recognized as a bearer of the surname Sharp, though specific widely known public details about him are not readily available.
-
C.
Laurence Skelly
Laurence Skelly is a Manx politician who has served as President of Tynwald, the parliament of the Isle of Man.
-
D.
Laurence Eusden
Laurence Eusden was an early 18th-century English poet best known for serving as one of the youngest and least acclaimed Poets Laureate of the United Kingdom.
-
E.
Laurence Boone
Laurence Boone is a French economist and diplomat who serves as France’s ambassador to the United States.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8946790d08190924d60bb4b523250 |
completed | April 10, 2026, 6:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e8a7b72c888190b069d0ebaebd31d9 |
completed | April 22, 2026, 10:49 a.m. |
Created at: April 8, 2026, 9:38 p.m.